Regularizing Neural Networks by Penalizing Confident Output Distributions
Gabriel Pereyra, George Tucker, Jan Chorowski, Łukasz Kaiser, and Geoffrey Hinton. 2017 · 2017
Later among the works it cites.
Get to the Point: Summarization with Pointer-Generator Networks
Abigail See, Peter J Liu, and Christopher D Manning. 2017 · 2017
Later among the works it cites.
Hybrid MemNet for Extractive Summarization
Abhishek Kumar Singh, Manish Gupta, and Vasudeva Varma. 2017 · 2017
Later among the works it cites.
Abstractive Document Summarization with a Graph-based Attentional Neural Model
Jiwei Tan, Xiaojun Wan, and Jianguo Xiao. 2017 · 2017
Later among the works it cites.
Attention is All You Need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Later among the works it cites.
Deep Communicating Agents for Abstractive Summarization
Asli Celikyilmaz, Antoine Bosselut, Xiaodong He, and Yejin Choi. 2018 · 2018
Closest in time.
A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents
Arman Cohan, Franck Dernoncourt, Doo Soon Kim, Trung Bui, Seokhwan Kim, Walter Chang, and Nazli Goharian. 2018 · 2018
Closest in time.
Bottom-up abstractive summarization
Sebastian Gehrmann, Yuntian Deng, and Alexander Rush. 2018 · 2018
Closest in time.
Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategies
Max Grusky, Mor Naaman, and Yoav Artzi. 2018 · 2018
Closest in time.
A Unified Model for Extractive and Abstractive Summarization using Inconsistency Loss
Wan-Ting Hsu, Chieh-Kai Lin, Ming-Ying Lee, Kerui Min, Jing Tang, and Min Sun. 2018 · 2018
Closest in time.
Content Selection in Deep Learning Models of Summarization
Chris Kedzie, Kathleen McKeown, and Hal Daume III. 2018 · 2018
Closest in time.
Generating Wikipedia by Summarizing Long Sequences
Peter J Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, and Noam Shazeer. 2018 · 2018
Closest in time.
Multi-Reward Reinforced Summarization with Saliency and Entailment
Ramakanth Pasunuru and Mohit Bansal. 2018 · 2018
Closest in time.
A Deep Reinforced Model for Abstractive Summarization
Romain Paulus, Caiming Xiong, and Richard Socher. 2018 · 2018
Closest in time.
Coloring with Limited Data: Few-shot Colorization via Memory-Augmented Networks
Seungjoo Yoo, Hyojin Bahng, Sunghyo Chung, Junsoo Lee, Jaehyuk Chang, and Jaegul Choo. 2019 · 2019
Closest in time.